Instructions to use HiTZ/BERnaT-Standard-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/BERnaT-Standard-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HiTZ/BERnaT-Standard-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/BERnaT-Standard-base") model = AutoModelForMaskedLM.from_pretrained("HiTZ/BERnaT-Standard-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93efb66eb10fa7bb094db3dc69a39ba3f7bea4e86fadc87cd98d087f3116bc06
- Size of remote file:
- 498 MB
- SHA256:
- 1f716b405898826dc48a138a1c0a0b14d5266b218a204ac7cbf3629fda848105
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